As social media websites gather ever-growing data stores, they might be better served by finding ways to make profitable use of that data instead serving ads as their chief means of raising revenue. While the data might give them the information they need to serve more targeted ads — although in my experience they still have a ways to go with that — the real value in the site could be the data itself.

Of course, if social sites start selling data to the highest bidder that leaves open questions of data ownership and privacy and finding ways to strip personal identifiers.

Marie Wallace (@marie_wallace) is social analytics strategist for the IBM Collaboration Solutions division. She has spent more than a decade at IBM working on content analytics, and her experience uniquely positions her to address questions regarding big data, social media and analytics. Our interview follows.

Social media's real value might not be in selling ads, but in the data they are collecting. Why do you think that is?

Marie Wallace: The reason ad targeting has worked so well for search is because it's aligned and supportive to that particular activity; when I am searching for information about products or services I am happy to get ads that may help direct my search. Ads are somewhat analogous to a value-added service and social search makes the ads more personalized and relevant, which is why Google has invested so heavily in Google+.

The key is that in most cases ads only work in a search-like context, however with most social media sites people are not going there to search. They are going to converse with friends and family, which makes ads interruptive and frequently invasive. This is further exacerbated by mobile, where limited real estate makes ads even more offensive as they are distracting and clutter the screen. Social search is one example of a service that sits on top of social data, but there are a whole plethora of other services that social data can drive — from market research to consumer/brand engagement, social recommenders, information filtering, or expertise location.

It's one thing to recognize the value of data, but how do you extract that value?

Marie Wallace: Extracting value from data requires a well-described set of scenarios with a clear understanding of what facts would be considered valuable for those scenarios. For example; when looking for a job there are a very specific set of questions that people want asked and answered: employee sentiment, corporate success (revenue, customers, products, growth), location, demographics, technologies, industries, skills, competitors, values, culture.

These are very different to the questions (and hence analysis) that might be pertinent to a different scenario. For example; when deciding where to go on holidays people are likely more interested in the location, activities, accommodation, weather, cost, demographics, or visitor sentiment. The key here is that analysis has to be not only domain-, but scenario-specific, which is why targeted specialist services like LinkedIn or Tripadvisor are always going to be able to deliver greater analytics value for the specific scenarios they support.

There are concerns on social networks about the sites abusing the data users are contributing. Is there a reliable way to anonymize data and deliver it in aggregate form that strips out individual user information?